A systems approach for modeling health information complexity. (December 2019) - Champion, Caitlin; Kuziemsky, Craig; Affleck, Ewan; Alvarez, Gonzalo G.
Highlights: Health information complexity impacts the implementation of information artifacts. To address health information complexity we first need systems based approaches to model it. We cannot look at clinical practice guidelines in isolation of other complexity factors. All information complexity is not the same but rather variations exist. Abstract: Information complexity issues such as poor data integration and quality and timely access to information can impair the implementation of information artifacts. Clinical practice guidelines (CPGs) are an information artifact used to guide a patient's care delivery over time. Despite evidence on the effectiveness of CPGs, they remain underutilized in certain contexts of medicine. One such example is colorectal cancer screening where disparities in screening rates and incidences of colorectal cancer are particularly prevalent between rural and urban populations. To address that issue, we need to better understand the information complexity factors that impact CPG implementation. This paper addresses the above shortcoming and uses a case study of colorectal cancer screening in remote and rural Northern Canada to develop a systems approach for modeling health information complexity. We describe a set of health information system components and interrelationships and a method for system mapping using the system components and interrelationships. We then provide exploratory system models from our case study and use them to characterize health information complexity according to interaction complexity and information behavior complexity. Our results highlight that information artifacts such as CPGs are not complex per se, but rather confounding factors is what causes information complexity. Our findings have implications for modeling information complexity and the design of policy and technological solutions to address health information complexity.